{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9686610f",
   "metadata": {},
   "source": [
    "# Feature importance and feature interaction based on partial dependece variance\n",
    "\n",
    "In this notebook example we will explain the global behavior of a regression model trained on a synthetic dataset. We will show how to compute the global feature attribution and the feature interactions for a given model.\n",
    "\n",
    "We will follow the example from [Greenwell et al. (2018)](https://arxiv.org/pdf/1805.04755.pdf)[[1]](#References) on the Friedman's regression problem defined in [Friedman et al. (1991)](https://projecteuclid.org/journals/annals-of-statistics/volume-19/issue-1/Multivariate-Adaptive-Regression-Splines/10.1214/aos/1176347963.full)[[2]](#References) and [Breiman et al. (1996)](https://link.springer.com/article/10.1007/BF00058655)[[3]](#References)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "939e3ab0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "from alibi.explainers.pd_variance import PartialDependenceVariance, plot_pd_variance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6879b947",
   "metadata": {},
   "source": [
    "### Friedman's regression problem\n",
    "\n",
    "Friedman's regression problem introduced in [Friedman et al.](https://projecteuclid.org/journals/annals-of-statistics/volume-19/issue-1/Multivariate-Adaptive-Regression-Splines/10.1214/aos/1176347963.full)[[2]](#References) and [Breiman et al.](https://link.springer.com/article/10.1007/BF00058655)[[3]](#References) consists in predicting a target variable based on ten independent features sample from a Uniform(0, 1). Although the feature space consists of ten features, only the first five of them appear in the true model. \n",
    "\n",
    "The relation between the input features and the response variables, $y$, is given by:\n",
    "\n",
    "$$\n",
    "y = 10 \\sin(\\pi x_1 x_2) + 20 (x_3 - 0.5)^2 + 10 x_4 + 5 x_5 + \\epsilon\n",
    "$$\n",
    "\n",
    "where $x_i$, for $i=1, ..., 10$ are the ten input features, and $\\epsilon \\sim \\mathcal{N}(0, \\sigma^2)$.\n",
    "\n",
    "In the following cell, we generate a dataset of 1000 examples which we split into 500 training examples and 500 testing examples. Similar to the paper setup, the simulated observation are generated using a $\\sigma=1$. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6f47e5a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_target(X: np.ndarray):\n",
    "    \"\"\"\n",
    "    Generates the target/response variable for the Friedman's regression problem.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    X\n",
    "        A matrix realisations sample from a Uniform(0, 1). The size of the matrix is `N x 10`,\n",
    "        where `N` is the number of data instances.\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    Response variable.\n",
    "    \"\"\"\n",
    "    return 10 * np.sin(np.pi * X[:, 0] * X[:, 1]) + 20 * (X[:, 2] - 0.5)**2 \\\n",
    "        + 10 * X[:, 3] + 5 * X[:, 4] + np.random.randn(len(X))\n",
    "\n",
    "np.random.seed(0)\n",
    "X = np.random.rand(1000, 10)\n",
    "y = generate_target(X)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ec474e3",
   "metadata": {},
   "source": [
    "### Train MLP regressor\n",
    "\n",
    "Similar with [Greenwell et al.](https://arxiv.org/pdf/1805.04755.pdf)[[1]](#References), we train a Muti-layer Perceptron (MLP) regressor and report its score on both the train and test split. For the purposes of this examples, we keep the default configuration for the `MLPRegressor`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "524be5f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train score: 0.968\n",
      "Test score: 0.931\n"
     ]
    }
   ],
   "source": [
    "# train MLP regressor on data\n",
    "nn = MLPRegressor(max_iter=10000, random_state=0)\n",
    "nn = nn.fit(X_train, y_train)\n",
    "\n",
    "# compute score on train and test dataset\n",
    "print(f\"Train score: {nn.score(X_train, y_train):.3f}\")\n",
    "print(f\"Test score: {nn.score(X_test, y_test):.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8becf509",
   "metadata": {},
   "source": [
    "### Define explainer\n",
    "\n",
    "Now that we have the prediction model, we can define the `PartialDependenceVariance` explainer to compute the feature importance and feature interactions.\n",
    "\n",
    "Note that our explainer can work with any black-box model by providing the prediction function, which in our case will be `nn.predict`. Furthermore, we can specify the feature names and the target names to match our formulation through the parameters `feature_names` and `target_names`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e2c1db23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define explainer\n",
    "explainer = PartialDependenceVariance(predictor=nn.predict,\n",
    "                                      feature_names=[f'x{i}' for i in range(1, 11)],\n",
    "                                      target_names=['y'],\n",
    "                                      verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ba00943",
   "metadata": {},
   "source": [
    "### Feature importance\n",
    "\n",
    "With our explainer initialized, we can compute the feature importance for all features through a simple call to the `explain` function. The arguments provided would be a reference dataset `X` which is usually the training dataset (i.e., `X_train` in our example) and setting `method='importance'`. Note that the `explain` function can receive many other arguments through which the user can specify explicitly the features to compute the feature importance for, the grid points (i.e., in our case `grid_resolution=50` to speed up the computation), etc. We refer the reader to our documentation page for further details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c01961db",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10/10 [00:00<00:00, 28.22it/s]\n"
     ]
    }
   ],
   "source": [
    "exp_importance = explainer.explain(X=X_train,\n",
    "                                   method='importance',\n",
    "                                   grid_resolution=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddae66b0",
   "metadata": {},
   "source": [
    "Once our explanation is computed, we can visualize the feature importance in two ways. `Alibi` implements an utility plotting function, `plot_pd_variance`, which helps the user quickly visualize the results.\n",
    "\n",
    "The simplest way is to visualize the results through a horizontal bar plot. By default, the features are ordered in descending order by their importance from top to bottom. This can be achieved through as simple call to `plot_pd_variance` as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f47607a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pd_variance(exp=exp_importance,\n",
    "                 features='all',\n",
    "                 fig_kw={'figwidth': 7, 'figheight': 5});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "686ba06a",
   "metadata": {},
   "source": [
    "We can see straight away that the explainer managed to identify that the first five features are the most salient (i.e., $x_4, x_2, x_1, x_3, x_5$ in decreasing order of their importance). \n",
    "\n",
    "As also recommended in the paper, the feature importance should be analyzed concomitantly with the Partial Dependence Plots (PDP) described in [Friedman et al. (2001)](https://projecteuclid.org/journals/annals-of-statistics/volume-29/issue-5/Greedy-function-approximation-A-gradient-boostingmachine/10.1214/aos/1013203451.full)[[4]](#Reference) and [Molnar (2020)]((https://christophm.github.io/interpretable-ml-book/pdp.html))[[5]](#References) based on which the importance has been calculated. Our utility function allows the user to visualize the PDPs by simply setting the parameter `summarise=False`. As before, the plots are sorted in descending order based on the corresponding feature importance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "91a4dbcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x1440 with 11 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pd_variance(exp=exp_importance,\n",
    "                 features='all',\n",
    "                 summarise=False,\n",
    "                 n_cols=3,\n",
    "                 fig_kw={'figwidth': 15, 'figheight': 20});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c07a10cc",
   "metadata": {},
   "source": [
    "From the PDPs, we can observe that the explainer managed to identify correctly the effects of each feature: linear for $x_4$ and $x_5$, quadratic for $x_3$, and sinusoidal for $x_1$ and $x_2$. The other variables show a relative flat main effect which according to the method's assumption means a low importance. Also, by inspecting the plots we can see that $x_4$ main effect spans a range from 8 to somewhere around 19, which is probably one of the reasons why it got the largest importance. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7fbfb41",
   "metadata": {},
   "source": [
    "### Feature interaction\n",
    "\n",
    "As previously mentioned, the `PartialDependenceVariance` explainer is able to compute a measure of feature interaction. The call to the explainer follows the same API as above, just by simply calling the `explain` function with the parameter `method='interaction'`. By default, the explainer will compute a measure of interaction for all possible pairs of features. Note that this is quadratic in the number of features and is based on computing a two-ways partial dependence function for all pairs. Thus, this step might be more computationally demanding. Similar with the computation of the feature importance, the user has the liberty to provide the features pairs for which the feature interaction will be computed and control the computation complexity through the grid parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "12a818dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 45/45 [00:34<00:00,  1.32it/s]\n"
     ]
    }
   ],
   "source": [
    "exp_interaction = explainer.explain(X=X_train,\n",
    "                                    method='interaction',\n",
    "                                    grid_resolution=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58507e1d",
   "metadata": {},
   "source": [
    "Once the explanation is computed, we can visualize the summary horizontal plot to identify the pairs of features that interact the most. Because the plot can grow very tall due to the quadratic number of feature pairs, we expose the `top_k` parameter to limit the plot to the `top_k` most important features provided through the `features` parameter. In our case we set `top_k=10` and since `features='all'`, the plot will display the 10 feature pairs that interact the most out of all feature pairs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e3ad5cb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot summary\n",
    "plot_pd_variance(exp=exp_interaction,\n",
    "                 features='all',    # considers plotting all features\n",
    "                 top_k=10,          # plots only the top 10 features from all the `features`\n",
    "                 fig_kw={'figwidth': 7, 'figheight': 5});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb36cdaf",
   "metadata": {},
   "source": [
    "From the plot above we can observe that the explainer attributes non-zero interaction values to many pairs of features, but interaction between $x_1$ and $x_2$ is the one that stands out, being an order of magnitude higher than the rest. This is in fact the only pair of features that interact through the function $\\sin(\\pi x_1 x_2)$.\n",
    "\n",
    "As before, if we would like to visualize more details, we can call again the `plot_pd_variance` with `summarise=False`. For each explained feature pair the function will plot the two-way PDP followed immediately by two conditional importance plots, when conditioning on one feature at a time. Note that the final interaction between the two features is computed as the average of the two conditional interactions (see titles of each subplot). For visualization purposes, we recommend using `n_cols=3`, such that each row will describe only the feature interaction between one pair. Similar as before, the plots are displayed in descending order based on their interaction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d65a1345",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x864 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pd_variance(exp=exp_interaction,\n",
    "                 features='all',  # considers plotting all feature pairs\n",
    "                 top_k=3,         # plots only the top 3 features pairs from all the `features`\n",
    "                 summarise=False,\n",
    "                 n_cols=3,\n",
    "                 fig_kw={'figwidth': 12, 'figheight': 12});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d297f1e4",
   "metadata": {},
   "source": [
    "We can observe that apart from the first plot corresponding to features $x_1$ and $x_2$, the other plots present an almost flat trend which can be an indication, but not a guarantee, of the absence of feature interaction. There exist functions for which the `PartialDependenceVariance` explainer does not capture the feature interaction. We refer the reader to the [method description](https://docs.seldon.io/projects/alibi/en/stable/methods/PartialDependenceVariance.html) for a more detailed example."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49956585",
   "metadata": {},
   "source": [
    "### References\n",
    "\n",
    "<a id='References'></a>\n",
    "\n",
    "[[1]](#source_1) Greenwell, Brandon M., Bradley C. Boehmke, and Andrew J. McCarthy. \"A simple and effective model-based variable importance measure.\" arXiv preprint arXiv:1805.04755 (2018).\n",
    "\n",
    "[[2]](#source_2) Friedman, Jerome H. \"Multivariate adaptive regression splines.\" The annals of statistics 19.1 (1991): 1-67.\n",
    "\n",
    "[[3]](#soruce_3) Breiman, Leo. \"Bagging predictors.\" Machine learning 24.2 (1996): 123-140.\n",
    "\n",
    "[[4]](#source_4) Friedman, Jerome H. \"Greedy function approximation: a gradient boosting machine.\" Annals of statistics (2001): 1189-1232.\n",
    "\n",
    "[[5]](#source_5) Molnar, Christoph. Interpretable machine learning. Lulu. com, 2020."
   ]
  }
 ],
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